Po-Sen Huang

Hello, and welcome to my website!

I am Po-Sen. I am a research scientist at Google DeepMind. Before DeepMind, I worked at Microsoft Research and Clarifai. I received my PhD from University of Illinois at Urbana-Champaign (UIUC), advised by Prof. Mark Hasegawa-Johnson. I received my B.S. degree from National Taiwan University.

Contacts

Email: p o s e n h u a n g AT company_name DOT com

Selected Publications (Google Scholar)

1. Alexander Novikov*, Ngân Vũ*, Marvin Eisenberger*, Emilien Dupont*, Po-Sen Huang*, Adam Zsolt Wagner*, Sergey Shirobokov*, Borislav Kozlovskii*, Francisco J. R. Ruiz, Abbas Mehrabian, M. Pawan Kumar, Abigail See, Swarat Chaudhuri, George Holland, Alex Davies, Sebastian Nowozin, Pushmeet Kohli, Matej Balog* (*Equal contribution)
   AlphaEvolve: A coding agent for scientific and algorithmic discovery
   Arxiv, 2025 (Paper, Blog)
2. Sumanth Dathathri*, Abigail See*, Sumedh Ghaisas*, Po-Sen Huang*, Rob McAdam*, Johannes Welbl, Vandana Bachani, Alex Kaskasoli, Robert Stanforth, Tatiana Matejovicova, Jamie Hayes, Nidhi Vyas, Majd Al Merey, Jonah Brown-Cohen, Rudy Bunel, Borja Balle, Taylan Cemgil, Zahra Ahmed, Kitty Stacpoole, Ilia Shumailov, Ciprian Baetu, Sven Gowal, Demis Hassabis, Pushmeet Kohli (*Equal contribution)
   Scalable watermarking for identifying large language model outputs
   Nature, 2024 (Paper, Blog, Code)
3. Ryutaro Tanno, David G. T. Barrett, Andrew Sellergren, Sumedh Ghaisas, Sumanth Dathathri, Abigail See, Johannes Welbl, Charles Lau, Tao Tu, Shekoofeh Azizi, Karan Singhal, Mike Schaekermann, Rhys May, Roy Lee, SiWai Man, Sara Mahdavi, Zahra Ahmed, Yossi Matias, Joelle Barral, S. M. Ali Eslami, Danielle Belgrave, Yun Liu, Sreenivasa Raju Kalidindi, Shravya Shetty, Vivek Natarajan, Pushmeet Kohli, Po-Sen Huang, Alan Karthikesalingam, Ira Ktena
   Collaboration between clinicians and vision–language models in radiology report generation
   Nature Medicine, 2024 (Paper)
4. Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d’Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals
   Competition-level code generation with AlphaCode
   Science, 2022 (Paper, Blog)
5. Amelia Glaese, Nat McAleese, Maja Trębacz, John Aslanides, Vlad Firoiu, Timo Ewalds, Maribeth Rauh, Laura Weidinger, Martin Chadwick, Phoebe Thacker, Lucy Campbell-Gillingham, Jonathan Uesato, Po-Sen Huang, Ramona Comanescu, Fan Yang, Abigail See, Sumanth Dathathri, Rory Greig, Charlie Chen, Doug Fritz, Jaume Sanchez Elias, Richard Green, Soňa Mokrá, Nicholas Fernando, Boxi Wu, Rachel Foley, Susannah Young, Iason Gabriel, William Isaac, John Mellor, Demis Hassabis, Koray Kavukcuoglu, Lisa Anne Hendricks, Geoffrey Irving
   Improving alignment of dialogue agents via targeted human judgements
   Arxiv, 2022 (Paper, Blog)
6. Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, Iason Gabriel
   Taxonomy of Risks posed by Language Models
   FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency (Paper, Blog)
7. Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew Johnson, Blake Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Ed Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving
   Scaling Language Models: Methods, Analysis & Insights from Training Gopher
   Arxiv, 2021 (Paper, Blog)
8. Po-Sen Huang, Minje Kim, Mark Hasegawa-Johnson, Paris Smaragdis
   Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
   IEEE/ACM Transactions on Audio, Speech, and Language Processing, Dec. 2015 (Paper, Code)
   [2020 IEEE SPS Best Paper Award]
9. Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, Larry Heck
   Learning Deep Structured Semantic Models for Web Search using Clickthrough Data
   Proc. of the ACM International Conference on Information and Knowledge Management (CIKM), 2013. (Paper, Code)
   [CIKM 2024 Test of Time Award]

Software

1. Scalable watermarking for identifying large language model outputs

1. Are Labels Required for Improving Adversarial Robustness?

1. Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation

1. Natural Language to Structured Query Generation via Meta-Learning

1. Towards Neural Phrase-based Machine Translation (NPMT)

1. Singing-Voice Separation From Monaural Recordings Using Robust Principal Component Analysis

1. Deep Learning for Monaural Source Separation